We have presented a novel method for human gait recognition, which is based on detecting the electrostatic induction current generated by the walking motion under non-contact conditions. The method involves the measurement of this electrostatic induction current, which flows through a measurement electrode. A model for the electrostatic induction current generated because of a change in the electric potential of the human body has been proposed. This model effectively explains the behavior of the waveform of the electrostatic induction current flowing through the electrode. Walking waveforms of 29 healthy individuals aged between 12 and 53 years were obtained. All the subjects wore rubber-soled shoes during the experiment. After Fourier analysis of the obtained waveform, the differentiated waveform of the gait spectrum was obtained in order to derive the subtle characteristics from the gait spectrum. The Pearson correlation coefficients with each other were obtained by data processing using methods such as differentiation and normalization. Results show that there is poor correlation between the walking waveforms. This suggests that the proposed technique based on the detection of subtle differences in the walking signal can be successfully applied for human identification.